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AI for insurers in 2021: Benefits, challenges and the path forward

Insurers have big ambitions for artificial intelligence (AI), which we define as computer systems that can sense their environment, then think, learn and take action in response. Here are the top findings from insurers who participated in our survey of US companies actively using AI: the top benefits they see, the top obstacles they report and how to overcome those obstacles.

AI for a better CX and forecasting

Among insurers who have already invested in AI, many are reaping big benefits: Almost two-thirds report success in using AI to create a better customer experience (CX). Nearly half say AI is helping improve decision-making. As reported by PwC specialists working with insurers on AI initiatives, companies are increasingly using AI to:

  • Customize products for both consumers and business customers 
  • Create more continual interaction with clients for greater loyalty and upselling 
  • Analyze more data from more sources (including social media) for better forecasts
  • Automate more aspects of claims processing
  • Enhance fraud detection and categorization
  • Conduct more sophisticated property and actuarial analyses

Yet many insurers who seek to deploy AI are getting stuck — usually in the same places.

Where AI investments are paying off for insurance companies
Bar chart illustrating To what degree have your AI investments in the following areas lived up to expectations?

Insurers face these AI obstacles

Insurers are concerned about some of the risks that AI solutions, if not carefully governed, could create: Potential new cybersecurity and privacy threats top the list of AI worries, cited by 42% and 36% of survey respondents, respectively. That may be why PwC’s AI experts report that insurers’ risk and regulatory teams frequently hit the brakes on initiatives.

The problem is not that AI is inherently risky. Instead, the challenge is that even if insurers’ risk and regulatory teams are typically highly sophisticated, they often lack the specialized technology skills and processes required to understand and model AI’s potential impacts.

Bar chart titled
Top AI threats over the next five years
AI creating new cyber threats
%
AI creating new privacy threats
%
Inability to meet demand for AI skills in our workforce
%
AI leading to new legal liabilities and reputational risks
%
The US falling significantly behind China or other countries in AI innovation
%
Unanticipated AI regulation
%
Customer distrust of AI leading to lost business
%
AI becoming too complex and/or intelligent to understand or control
%
Societal backlash against AI
%
AI disrupting one or more of the geographical markets in which we operate
%
AI disrupting one or more of the sectors in which we operate
%
Q: Which of the following scenarios related to AI do you perceive as a threat within the next 5 years? Source: PwC AI Predictions 2021. Base: 56

The lack of AI skills is, of course, a more general challenge, which doesn’t just hold back initiatives for technical reasons. It can create cultural barriers too: Executives may hesitate to greenlight or use tools that they don’t feel comfortable with.

Another common problem is silos, among business lines and between AI and analytics groups. They all need to work together, both to give AI the data it needs and to help initiatives scale up faster.

How insurers can accelerate AI

The following four guidelines can help insurers overcome the obstacles and achieve faster ROI with AI:

  1. Focus on data. Collecting the right data, cleaning it up and standardizing it, and making it available are critical to rapidly and reliably deploying AI.

  2. Centralize capabilities. Bring AI, analytics and automation together to help allocate resources, standardize and utilize data, improve governance and scale solutions.

  3. Think long term. When you start now on developing key capabilities, such as AI upskilling, you’ll likely see benefits for years to come.

  4. Make AI responsible AI. To reduce AI’s risks and make it explainable, apply the responsible AI toolkit.

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Matt Adams

Insurance Practice Leader, New York, PwC US

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Marie Carr

Global Growth Strategy, US Financial Services Practice, Chicago, PwC US

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Anand Rao

Global AI Lead; US Innovation Lead, Emerging Technology Group, Boston, PwC US

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